DBMS > Drizzle vs. GeoSpock vs. GigaSpaces vs. Riak TS vs. Yaacomo

System Properties Comparison Drizzle vs. GeoSpock vs. GigaSpaces vs. Riak TS vs. Yaacomo

Editorial information provided by DB-Engines

Name

Drizzle has published its last release in September 2012. The open-source project is discontinued and Drizzle is excluded from the DB-Engines ranking.

GeoSpock seems to be discontinued. Therefore it will be excluded from the DB-Engines ranking.

Yaacomo seems to be discontinued and is removed from the DB-Engines ranking

Description

MySQL fork with a pluggable micro-kernel and with an emphasis of performance over compatibility.

Spatial and temporal data processing engine for extreme data scale

High performance in-memory data grid platform, powering three products: Smart Cache, Smart ODS (Operational Data Store), Smart Augmented Transactions

Riak TS is a distributed NoSQL database optimized for time series data and based on Riak KV

OpenCL based in-memory RDBMS, designed for efficiently utilizing the hardware via parallel computing

Primary database model

Relational DBMS

Document store
Object oriented DBMS

Values are user defined objects

Time Series DBMS

Relational DBMS

Secondary database models

Time Series DBMS

Graph DBMS
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Trend Chart

Score	0.97
Rank	#192	Overall
	#32	Document stores
	#6	Object oriented DBMS

Score	0.20
Rank	#319	Overall
	#27	Time Series DBMS

Website

geospock.com

www.gigaspaces.com

yaacomo.com

Technical documentation

docs.gigaspaces.com/latest/landing.html

www.tiot.jp/riak-docs/riak/ts/latest

Developer

Drizzle project, originally started by Brian Aker

GeoSpock

Gigaspaces Technologies

Open Source, formerly Basho Technologies

Q2WEB GmbH

Initial release

2008

2000

2015

2009

Current release

7.2.4, September 2012

2.0, September 2019

15.5, September 2020

3.0.0, September 2022

License

Commercial or Open Source

Open Source

GNU GPL

commercial

Open Source

Apache Version 2; Commercial licenses available

Open Source

commercial

Cloud-based only

Only available as a cloud service

yes

DBaaS offerings (sponsored links)

Database as a Service

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Implementation language

C++

Java, Javascript

Java, C++, .Net

Erlang

Server operating systems

FreeBSD
Linux
OS X

hosted

Linux
macOS
Solaris
Windows

Linux
OS X

Android
Linux
Windows

Data scheme

yes

schema-free

yes

Typing

predefined data types such as float or date

yes

XML support

Some form of processing data in XML format, e.g. support for XML data structures, and/or support for XPath, XQuery or XSLT.

XML can be used for describing objects metadata

Secondary indexes

yes

temporal, categorical

yes

restricted

yes

SQL

Support of SQL

yes

with proprietary extensions

ANSI SQL for query only (using Presto)

SQL-99 for query and DML statements

yes, limited

yes

APIs and other access methods

JDBC

GigaSpaces LRMI
Hibernate
JCache
JDBC
JPA
ODBC
RESTful HTTP API
Spring Data

HTTP API
Native Erlang Interface

JDBC
ODBC

Supported programming languages

C
C++
Java
PHP

.Net
C++
Java
Python
Scala

unofficial client library
C#
C++

unofficial client library
Clojure

unofficial client library
Dart

unofficial client library
Erlang
Go

unofficial client library
Groovy

unofficial client library
Haskell

unofficial client library
Java
JavaScript

unofficial client library
Lisp

unofficial client library
Perl

unofficial client library
PHP
Python
Ruby
Scala

unofficial client library
Smalltalk

unofficial client library

Server-side scripts

Stored procedures

yes

Erlang

Triggers

hooks for callbacks inside the server can be used.

yes, event driven architecture

yes

pre-commit hooks and post-commit hooks

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

Automatic sharding

Sharding

horizontal partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication
Source-replica replication

Multi-source replication

synchronous or asynchronous
Source-replica replication

synchronous or asynchronous

selectable replication factor

Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Map-Reduce pattern can be built with XAP task executors

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Consistency level configurable: ALL, QUORUM, ANY

Eventual Consistency

Immediate Consistency

Foreign keys

Referential integrity

yes

links between datasets can be stored

yes

Transaction concepts

Support to ensure data integrity after non-atomic manipulations of data

ACID

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

In-memory capabilities

Is there an option to define some or all structures to be held in-memory only.

yes

User concepts

Access control

Pluggable authentication mechanisms

e.g. LDAP, HTTP

Access rights for users can be defined per table

Role-based access control

fine grained access rights according to SQL-standard

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More resources

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